Changes in vegetation spring dates in the second half of the twentieth century

Abstract

This study aims at estimating trends in spring phenology from vegetation index and air temperature at 2m height. To this end, we have developed a methodology to infer spring phenological dates from Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) time-series, which are then extrapolated to the period 1948-2006 with the help of Reanalysis data, using its 2m height air temperature parameter. First, yearly NDVI is fitted to a double-logistic function for the whole extent of the GIMMS database (1981-2003). This fitting procedure allows us to describe, on a yearly basis, the NDVI evolution for each pixel through the estimation of six parameters which include the spring date. Retrieved spring date time-series are then upscaled to Reanalysis database resolution and compared to degree-day amounts. Those degree-day amounts are estimated for various thresholds in order to determine the best thresholds for their calculations on a pixel-by-pixel b